Digital map shape vector encoding method and position information transfer method

ABSTRACT

It is an object to provide a method of coding the position information of a digital map in a small data volume by utilizing a compressing and coding technique. In a coding method of coding data indicative of a shape vector on a digital map, an arithmetic processing is carried out over position information about a node string and a shape which indicate the shape vector to be represented by data having a statistical deviation, and the data having the statistical deviation are coded to reduce a data volume. It is possible to considerably decrease a transmission data volume in the case in which the vector shape of the digital map is to be transferred.

TECHNICAL FIELD

[0001] The present invention relates to a method of transmittingposition information of a digital map, a coding method of compressingand coding the data volume of data to be transmitted and a devicethereof, and more particularly to a reduction in a data volume by usinga compression and coding technique.

BACKGROUND ART

[0002] In the case in which traffic information is to be provided to anavigation onboard machine for mounting a digital map data base,conventionally, a road is specified by a link number and a node such asan intersection present on the road is specified by a node number and apoint on the road is transmitted in such a method as to represent adistance from the node in such a manner that a position on the digitalmap is accurately transmitted even if a transmitting side and areceiving side hold digital maps created by different sources.

[0003] However, the node number and the link number which are defined ina road network are to be changed to new numbers corresponding to the newprovision or alteration of a road. Moreover, the digital map data ofeach company to be a creation source are to he also updatedcorrespondingly. Therefore, the methods using the node number and thelink number require a large social cost for maintenance.

[0004] In order to improve such a respect, the inventors of theinvention have proposed the following digital map position informationtransmitting method in JP-A-11-214068 and JP-A-11-242166.

[0005] In such a method, when the information providing side is totransmit the position of a road in which an event such as a traffic jamor a traffic accident is caused, “road shape data” comprising thecoordinate string of a node and an interpolation point (the vertex of apolygonal line approximating the curve of the road which will bereferred to as a “node” including the interpolation point if there is norestriction in this specification) arranged on the road taking a shapein a road section having a predetermined length which includes the eventposition and “event position data” indicative of the event positionbased on a relative position in the road section represented by the roadshape data are transmitted to the receiving side, the side receivingthese information carries out map matching by using the road shape datato specify the road section on a self-digital map, thereby specifying anevent generation position in the road section by using the eventposition data.

[0006]FIG. 43 illustrates the “road shape data” and FIG. 44 illustratesthe “event position data”.

[0007] In a method of transmitting the position information of thedigital map by using the “road shape data” and the “event positiondata”, however, there is a problem in that the data volume of the roadshape data for specifying the shape of a road is increased and theamount of data transmission is thereby increased.

[0008] As a method of reducing the data volume of the road shape data,the inventors of the invention has proposed a method of approximatingthe shape of a road by a spline function in JP-A-2001-12127. In order tofix the position information transmitting method, it is necessary tofurther promote a reduction in the data volume.

[0009] The invention solves such a problem and has an object to providea position information transmitting method of transmitting positioninformation of a digital map in a small data volume by utilizing acompression and coding technique, a coding method of reducing a datavolume and a device for executing the methods.

SUMMARY OF THE INVENTION

[0010] The invention provides a coding method of coding datarepresenting a shape vector on a digital map, wherein an arithmeticprocessing is carried out over position information about each node of anode string representing the shape vector, the position information isconverted into data having a statistical deviation, and the data arecoded to reduce a data volume.

[0011] Moreover, in a position information transmitting method for adigital map in which a transmitting side transmits shape datarepresenting a shape vector on the digital map and a receiving sidecarries out map matching based on the received shape data and specifiesthe shape vector on a self-digital map, wherein the transmitting sidetransmits shape vector data coded by the coding method and the receivingside decodes the received data and reproduces a shape, and specifies ashape vector corresponding to the reproduced shape by the map matching.

[0012] Furthermore, a transmitter for transmitting, to a receiving side,shape data representing a shape vector on a digital map comprises codetable calculating means for carrying out an arithmetic processing overposition information of each node of a node string representing theshape vector on the digital map, converting the position informationinto data having a statistical deviation and generating a code tableusing coding for the data based on an occurrence distribution of thedata, and position information converting means for coding positioninformation of each node of the shape vector to be transmitted to thereceiving side by using the code table and for generating shape data tobe transmitted to the receiving side.

[0013] Moreover, a receiver for receiving coded data representing ashape vector on a digital map from a transmitting side comprises codedata decoding means for decoding the received data which are coded andfor reproducing shape data represented by position information on thedigital map, and map matching means for carrying out map matching byusing the shape data thus reproduced, thereby specifying the shapevector on a self-digital map.

[0014] Consequently, the data volume of the shape vector in the digitalmap can be compressed efficiently and the volume of data to betransferred can considerably be decreased when the shape vector of thedigital map is to be transmitted. On the receiving side, the shape dataare reconstituted from the received data and the map matching isexecuted so that the transmitted shape vector can be specifiedaccurately.

BRIEF DESCRIPTION OF THE DRAWINGS

[0015]FIG. 1 is a diagram showing a node resampled in the case in whicha coding method according to a first embodiment is applied,

[0016]FIG. 2 is a code table in the coding method according to the firstembodiment,

[0017]FIG. 3 is a run-length code table to be used in a coding methodaccording to a second embodiment,

[0018]FIG. 4 is a code table for Δθ to be used in the coding methodaccording to the second embodiment,

[0019]FIG. 5 is a code table for Δθ to take a run-length intoconsideration which is to be used in the coding method according to thesecond embodiment,

[0020]FIG. 6 is a block diagram showing the structure of a device forexecuting a position information transmitting method according to athird embodiment,

[0021]FIG. 7 is a flow chart showing a code table creating procedure ina coding method according to the third embodiment,

[0022]FIG. 8 is a flow chart showing a shape data creating procedure ina coding method according to the third embodiment,

[0023]FIG. 9 is a table showing the structure of shape vector datastring information for specifying road/section as transmitted data inthe position information transmitting method according to the thirdembodiment,

[0024]FIG. 10 is a table showing the structure of various trafficinformation represented by relative distance from each node on shapevector data as transmitted data in the position information transmittingmethod according to the third embodiment,

[0025]FIG. 11 is a flow chart showing a processing procedure on thereceiving side in the position information transmitting method accordingto the third embodiment,

[0026]FIG. 12 is a diagram showing the relationship between a samplesection length and the curvature of shape data in a coding methodaccording to a fourth embodiment,

[0027]FIG. 13 is a chart for explaining a circular arc and straight-lineapproximation in the coding method according to the fourth embodiment,

[0028]FIG. 14 is a diagram showing a section partitioned in the codingmethod according to the fourth embodiment,

[0029]FIG. 15(a) is a flow chart showing a method of determining aresample section length in the coding method according to the fourthembodiment,

[0030]FIG. 15(b) is a diagram showing a table which is referred in theflow chart showed in FIG. 15(a),

[0031]FIG. 16 is a diagram for explaining quantization resampling in thecoding method according to the fourth embodiment,

[0032]FIG. 17 is a diagram for explaining the candidate point of a nextnode in the coding method according to the fourth embodiment,

[0033]FIG. 18 is a flow chart showing a node determining procedure inthe coding method according to the fourth embodiment,

[0034]FIG. 19 is a code table in the coding method according to thefourth embodiment,

[0035]FIG. 20 is a flow chart showing a code table creating procedure inthe coding method according to the fourth embodiment,

[0036]FIG. 21 is a flow chart showing a shape data creating procedure inthe coding method according to the fourth embodiment,

[0037]FIG. 22 is a table showing the structure of transmitted data in aposition information transmitting method according to the fourthembodiment,

[0038]FIG. 23(a), (b), (c) are diagrams typically showing thetransmission of data in the coding method according to the fourthembodiment,

[0039]FIG. 24 is a flow chart showing a processing procedure on thereceiving side in the position information transmitting method accordingto the fourth embodiment,

[0040]FIG. 25 is a diagram showing a node position, a distance and angleinformation to which a coding method according to a fifth embodiment isapplied,

[0041] FIGS. 26(a), (b) is a code table to be used in the coding methodaccording to the fifth embodiment,

[0042]FIG. 27 is a flow chart showing a code table creating procedure inthe coding method according to the fifth embodiment,

[0043]FIG. 28 is a flow chart showing a shape data creating procedure inthe coding method according to the fifth embodiment,

[0044]FIG. 29 is a table showing the structure of shape vector datastring information for specifying road/section as transmitted data in aposition information transmitting method according to the fifthembodiment,

[0045]FIG. 30 is a table showing the structure of various trafficinformation represented by relative distance from each node on shapevector data in a position information transmitting method according tothe fifth embodiment,

[0046]FIG. 31 is a diagram showing a node position, a distance and angleinformation in the case in which a coding method according to a sixthembodiment is applied,

[0047]FIG. 32 is a code table to be used in the coding method accordingto the sixth embodiment,

[0048]FIG. 33 is a flow chart showing a code table creating procedure inthe coding method according to the sixth embodiment,

[0049]FIG. 34 is a flow chart showing a shape data creating procedure inthe coding method according to the sixth embodiment,

[0050]FIG. 35 is a table showing the structure of shape vector datastring information for specifying road/section as transmitted data in aposition information transmitting method according to the sixthembodiment,

[0051]FIG. 36 is a view showing the shape of a road which is suitablefor applying a coding method according to a seventh embodiment,

[0052]FIG. 37 is a flow chart showing a θ code table creating procedurein the coding method according to the seventh embodiment,

[0053]FIG. 38 is a flow chart showing a Δθ code table creating procedurein the coding method according to the seventh embodiment,

[0054]FIG. 39 is a flow chart showing a shape data creating procedure inthe coding method according to the seventh embodiment,

[0055]FIG. 40 is a table showing the structure of shape vector datastring information for specifying road/section as transmitted data in aposition information transmitting method according to the seventhembodiment,

[0056]FIG. 41 is a diagram for explaining a distance and an angle whichspecify a coordinate point,

[0057] FIGS. 42(a) and (a′) are a diagram and a chart which show thefull curvature function representation of shape data,

[0058] FIGS. 42(b) and (b′) are a diagram and a chart which show thedeflection angle representation of the shape data,

[0059] FIGS. 42(c) and (c′) are a diagram and a chart showing thepredicted value difference representation of a deviation angle of theshape data, and

[0060]FIG. 43 is a table showing a data structure of shape vector datestring information in a conventional position information transmittingmethod,

[0061]FIG. 44 is a table showing a data structure of traffic informationin a conventional position information transmitting method.

[0062] Additionally, the reference numerals in the drawings, 10 and 30show online processing portion, 11 shows event information inputportion, 12 shows digital map display portion, 13 and 22 show digitalmap data base, 14 shows map matching portion, 15 shows positioninformation converting portion, 16 shows position informationtransmitting portion, 17 shows position information receiving portion,18 shows code data decompressing portion, 20 shows offline processingportion, 21 shows past traffic information, 23 shows code tablecalculating portion, 24 shows code table data, and 40 shows a road.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0063] (First Embodiment)

[0064] In a first embodiment, description will be given to a method ofcompressing data by variable-length coding.

[0065] In a method of transmitting position information of a digital mapaccording to the invention, first of all, the shape of a road isexpressed in shape data having a statistical deviation. The reason isthat a compressibility is to be increased when the shape data arecompressed and coded.

[0066] In the case in which the shape of the road is to be representedby a coordinate point arranged on the road, the position of eachcoordinate point (P_(J)) can be uniquely specified by two dimensions ofa distance from an adjacent coordinate point (P_(J−1)) and an angle asshown in FIG. 41 In FIG. 41, the angle indicates an angle Θ_(j) based onan “absolute azimuth” for setting a due north (upper in the drawing)azimuth to 0 degree and designating an angle of 0 to 360 degreesclockwise. Thus, the expression of a coordinate point by using thedistance and the absolute azimuth is referred to as a full curvaturefunction representation.

[0067] When x and y coordinates of coordinate points P_(J−1), P_(J) andP_(J+1) are set to (x_(j−1), y_(j−1)), (x_(j), y_(j)) and (x_(j+1),y_(j+1)), a distance L_(j) (a distance between the coordinate pointsP_(J) and P_(J+1)) and the absolute angle Θ_(j) (the absolute azimuth ofa straight line extended from the coordinate point P_(J) to thecoordinate point P_(J+1)) can be calculated by the following equations.

L _(j)={square root}{square root over ( )}{(x _(j+1) −x _(j))²+(y _(j+1)−y _(j))²}

Θ_(j)=tan⁻¹{(x _(j+1) −x _(j))/(y _(j+1) −y _(j))}

[0068] In the case in which a new coordinate point is reset (resampled)such that a distance from an adjacent coordinate point is constant (=L)over the shape of the road, information about the angle Θ_(j) (that is,information about one dimension) is simply transmitted for theindividual coordinate points so that the position of the coordinatepoint can be specified on the receiving side to reduce the volume ofdata to be transmitted in addition to common information about L.

[0069]FIG. 42(a) shows the absolute azimuth Θ_(j) on each coordinatepoint (P_(J)) in the case in which the coordinate point is resampled insuch a position that a distance from an adjacent coordinate point on theroad is constant (=L) In the case in which each coordinate point isrepresented by the absolute azimuth Θ_(j), the frequency of generationof the angle information Θ_(j) indicative of each coordinate point doesnot have a statistical deviation as shown in FIG. 42(a′) .

[0070] However, the angle of each coordinate point can also berepresented by a difference in a displacement of the absolute azimuth,that is, a “deviation angle” θ_(j) as shown in FIG. 42(b). The deviationangle θ_(j) can be calculated as follows.

θ_(j)=Θ_(j)−Θ_(j−1)

[0071] In the case in which each coordinate point is represented by thedeviation angle θ_(j), the frequency of generation of the angleinformation θ_(j) indicative of each coordinate point has a maximumvalue for θ=0 degree as shown in FIG. 42(b′) in a region having a largenumber of straight roads.

[0072] Moreover, the angle of each coordinate point can also berepresented by a difference Δθ_(j) between the deviation angle θ_(j) anda deviation angle statistical predicted value S_(j) (a predicted valuerepresented by a deviation angle) as shown in FIG. 42(c). The deviationangle statistical predicted value S_(j) is obtained by estimating thedeviation angle θ_(j) of the coordinate point P_(J) to be noted throughthe deviation angles of previous coordinate points up to P_(J−1). Forexample, the deviation angle statistical predicted value S_(j) can bedefined as

S _(j)=θ_(j−1)

[0073] or

S _(j)=(θ_(j−1)+θ_(j−2))/2.

[0074] Moreover, the deviation angle statistical predicted value S_(j)may be defined by setting the weighted mean of the deviation angles onpast n coordinate points to be S_(j). The predicted value differenceΔθ_(j) of the deviation angle is calculated as

Δθ_(j)=θ_(j) −S _(j).

[0075] Most of the road shapes are straight lines or are gentle curves.In the case in which a distance L between the coordinate points is setto be constant, therefore, the predicted value difference Δθ_(j) of thedeviation angle concentrates in the vicinity of 0 degree so that thefrequency of generation of angle information Δθ_(j) indicative of eachcoordinate point has a great deviation around θ=0 degree as shown inFIG. 42(c′).

[0076] In order to obtain shape data having a statistical deviation, theroad shape (original shape) is sampled at regular intervals in theresample section length L having a constant distance and position dataof a sampling point (node) P_(J) are represented by the predicted valuedifference Δθ_(j)(=θ_(j) −S _(j)) of the deviation angle θ_(j). Thedistance may be an actual distance obtained by expansion into an outsideworld or a length expressed in a unit of predetermined normalizedcoordinates.

[0077] It is defined that the deviation angle statistical predictedangle S_(j) is set to

Sj=(θ_(j−1)+θ_(j−2))/2.

[0078] Since the shape of the road is curved gently in most cases,

θ_(j)≠(θ_(j−1)+θ_(j−2))/2=S _(j).

[0079] Consequently, it can be supposed that Δθ_(j) is distributedwithin a very small range around 0.

[0080] Theoretically, the Δθ_(j) can have a value of −360 degrees to+360 degrees. For this reason, 10 bits obtained by adding 1 bitrepresenting a positive or negative sign and 9 bits representing anumeric value of 360 are required for expressing Δθ_(j) with a 1°resolution. By coding an angle in the vicinity of ±0 degree with asmaller value than 10 bits and assigning a greater value than 10 bits toan angle set apart from ±0 degree, a mean bit number to be used forcoding Δθ_(j) can be set to be smaller than 10 bits and the shape datacan be expressed in a small data volume in total.

[0081]FIG. 2 illustrates a code table in which a code for coding isassigned to the Δθ. If Δθ=0 is set, coding to zero is carried out. IfΔθ=+1 is set, an overhead bit of 0 representing a positive sign is addedto a code 100 to obtain 1000. If Δθ=−1 is set, an overhead bit of 1representing a negative sign is added to the code 100 to obtain 1001.

[0082] The variable-length coding will be described with reference toFIG. 1. If a node number is 6 (=a start edge+5 nodes), normal codingrequires a data volume having a fixed length of 5×10 bits=50 bits inaddition to an initial value angle (10 bits). On the contrary, in thecase of coding using the code table shown in FIG. 2, if it is assumedthat Δθ_(j) takes a value of 0 three times and a value which is equal toor less than ±2 degrees twice, the data volume can be expressed in 3×1bit=2×4 bits=11 bits in addition to the initial value angle (10 bits).If the data are “0, 0, +1, −2, 0”, they can be expressed in“001000101100” by the coding.

[0083] The receiving side can obtain each value of Δθ_(j) by applyingthe value of Δθ in order with reference to a code table which is senttogether with the shape data (or is previously held). By sequentiallycarrying out integration from an initial value, the value of thedeviation angle θ_(j) on each coordinate point can be decided uniquely.

[0084] The code table is created by calculating an angle of Δθ_(j) oneach coordinate point P_(J), checking the frequency of generation of theangle and using the well-known Huffman tree depending on the frequencyof generation.

[0085] Thus, an arithmetic processing is carried out over the shape datato have a statistical deviation and the variable-length coding is thenperformed. Consequently, the data volume of the shape data can bereduced.

[0086] While the resampled node position is represented by the distancebetween the adjacent nodes and the deviation angle, the sampled nodeposition at regular intervals in the resample section length L can alsobe expressed in relative latitude and longitude coordinates (Δx_(j),Δy_(j)). In this case, the statistical value S_(j) is expressed in

Δx _(j) =S _(jx) +δx _(j) =Δx _(j−1) +δx _(j)

Δy _(j) =S _(jy) +δy _(j) =Δy _(j−1) +δy _(j)

[0087] on a definition of S_(jx)=Δx_(j−1) and S_(jy)=Δy_(j−1), andδx_(j) and δy_(j) are variable-length coded and are thus transmitted asthe shape data.

[0088] (Second Embodiment)

[0089] In a second embodiment, description will be given to a method ofcompressing data by using a run-length method.

[0090] In the example of the first embodiment, in the case in whichΔθ_(j) is coded to express the shape data, “0” continues in a straightroad or a road curved with the same curvature. In such a case, a datacompressibility is higher in an expression of “0 continues twenty times”than “00000 . . . ”. Herein, run-length coding is carried out tocompress data.

[0091]FIG. 3 shows a code table for the run-length which defines thatthe same number continuing five times (a run-length of 5) is displayedas “101”, for example. FIG. 4 shows the same code table for Δθ as thatin FIG. 2.

[0092] A data array is determined as run-length →Δθ→ run-length →Δθ→. .. , for example. When Δθ is

[0093] “0, 0, 0, 0, 0, −2, −2, 0, +3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, −1 . . . ”,

[0094] it is expressed in “101·0_(—)0·1011_(—)0·1011_(—)0·0_0·11000_(—)1101·0_(—)0·1001 . . . ”→

[0095] “10100101101011000110001101001001 . . . ” (32 bits) by arun-length method.

[0096] On the other hand, in the case in which the run-lengthrepresentation is not used,

[0097] “000001011101101100000000000000000001001 . . . ” (38 bits) isset.

[0098] Moreover, the code tables shown in FIGS. 3 and 4 can berestricted to specifically effective tables and can also be collectedinto one code table as shown in FIG. 5. In FIG. 5, the run-length isdefined in only the case of Δθ=0. By using the code table in FIG. 5,

[0099] “0, 0, 0, 0, 0, −2, −2, 0, +3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, −1 . . . ” can be expressed in

[0100] “100·11101·11101·0·111100·1100·11011 . . .”→“10011101111010111100110011011 . . . ” (29 bits).

[0101] In this connection, as compared with an expression method for afixed length of 1 node and 10 bits, 10 bits×25 nodes=250 bits isobtained. It is apparent that compression to 29∵250=12% is carried outin this example.

[0102] (Third Embodiment)

[0103] In a third example, description will be given to a device forexecuting the position information transmitting method according to theinvention.

[0104]FIG. 6 shows a position information transmitter/receiver forexchanging event generation information on a road together with anotherdevice 30 as an example of the device.

[0105] The device comprises an offline processing portion 20 forgenerating a code table to be used for compressing and coding road shapedata in an offline, and an online processing portion 10 for transmittingtraffic information by using the code table data generated by theoffline processing portion 20. The offline processing portion 20includes a digital map data base 22, a storage portion 21 for storingpast traffic information, a code table calculating portion 23 forgenerating code table data to be used for compression and coding, and acode table data base 24 for storing the code table data thus generated.

[0106] On the other hand, the online processing portion 10 includes aposition information receiving portion 17 for receiving “road shapedata” and “event position data” which are compressed and coded from aposition information transmitting portion 16 of the device 30, a codedata decompressing portion 18 for decompressing (decoding) thecompressed and coded data, a digital map data base 13 for storingdigital map data, a map matching portion 14 for carrying out mapmatching by using the road shape data and the event position data whichare decompressed and for specifying an event position on a self-digitalmap, a digital map display portion 12 for superposing and displaying theevent position on the map, an event information input portion 11 forinputting information about a generated event, a position informationconverting portion 15 for determining an object road section includingan event position, generating “event position data” representing theevent position as the relative position of the object road section andcompressing and coding the shape data of the object road section byusing the code table data 24, thereby generating “road shape data”, anda position information transmitting portion 16 for transmitting thegenerated “road shape data” and “even position data” to a positioninformation receiving portion 17 of the device 30.

[0107] Flow charts in FIG. 7 and FIG. 8 show the procedure of theoperation of the device. In the offline processing portion 20, the codetable calculating portion 23

[0108] Step 1: refers to the past traffic information 21,

[0109] Step 2: selects the object road section of the trafficinformation, and

[0110] Step 3: resamples the shape data of the object road section in afixed length L, thereby setting a node as shown in FIG. 7.

[0111] Step 4 Convert position data on the node to a full curvaturefunction representation.

[0112] Step 5: Calculate Δθ of each section/each node in accordance witha statistical value calculating equation.

[0113] Step 6: Next, calculate the occurrence distribution of Δθ.

[0114] Step 7: Then, calculate the continuous distribution of the samevalue.

[0115] Step 8: Create a code table based on the occurrence distributionof Δθ and the continuous distribution of the same value.

[0116] Step 9: Store the finished code table in the code table data base24.

[0117] The processing procedure is defined by a program for causing thecomputer of the offline processing portion 20 to function as the codetable calculating portion 23.

[0118] In the online processing portion 10, moreover, the positioninformation converting portion 15

[0119] Step 10: receives the traffic information from the eventinformation input portion 11,

[0120] Step 11: selects an object road section including the position ofgeneration of the traffic event, and

[0121] Step 12: resamples the shape data of the object road section in afixed length L, thereby setting a node as shown in FIG. 8.

[0122] Step 13: Convert position data on the node into a full curvaturefunction representation.

[0123] Step 14: Calculate Δθ of each section/each node in accordancewith a statistical value calculating equation.

[0124] Step 15: convert the shape data into a code representation byreferring to the code table data 24 of a code table created to beintended for the object road section (or a code table created to beintended for a road having a shape to approximate the object roadsection).

[0125] Step 16: Transmit the shape data on the object road section whichare coded together with data on an event position represented byrelative information about the object road section.

[0126] The processing procedure is defined by a program for causing thecomputer of the online processing portion 10 to function as the positioninformation converting portion 15.

[0127]FIG. 9 and FIG. 10 show road shape data (FIG. 9) and eventposition data (FIG. 10) which are to be transmitted. The road shape datainclude code table data, data on the section length L which areresampled, and shape data which are compressed and coded.

[0128]FIG. 11 shows the processing procedure of the receiving side whichreceives the data.

[0129] Step 20: When the position information receiving portion 17receives position information,

[0130] Step 21: the code data decompressing portion 18 reconstitutescoded data by referring to a code table included in the received dataand converts shape data into a full curvature function.

[0131] Step 22: Next, shape data expressed in latitude and longitudecoordinates are reproduced.

[0132] Step 23: The map matching portion 14 executes map matching withthe reproduced shape and the road shape of a self-digital map to specifyan object road section, and furthermore, to specify a traffic eventgeneration position in the object road section from event position data.

[0133] Step 24: The digital map display portion 12 superposes anddisplays traffic information on the map.

[0134] The processing procedure is defined by a program for causing thecomputer of the online processing portion 10 to function as the codedata decompressing portion 18 and the map matching portion 14.

[0135] While the code table used in the compression and coding isincluded in the data to be transmitted and is thus transmitted, it isnot necessary to include the code table in the data to be transmitted bycausing the transmitting and receiving sides to previously have the samecode table.

[0136] There has been described the example in which the code table data24 created by the offline processing portion 20 are utilized to obtainthe shape data compressed and coded by the online processing portion 10.The offline processing portion 20 compresses and codes each road shapeof an object region and previously holds the shape data of each roadsection which are represented by a code. When acquiring informationabout the generation of a traffic event, the online processing portion10 may select the road shape data coded in the road section including atraffic event generation position from the shape data held in theoffline processing portion 20, generate traffic information in which thetraffic event generation position is represented by the relativeposition of the road section and transmit, to the receiving side, thecoded road shape data thus selected and the generated trafficinformation.

[0137] In this case, the offline processing portion 20 resamples theshape data of the road section to be a coding object in a fixed length Lin the procedure of Steps 2 to 9, calculates Δθ in each node and createsa code table based on the occurrence distribution of Δθ. By using thecode table thus created, next, Δθ on each coordinate point which isresampled is converted into a code representation and compressed andcoded shape data are created and are stored in a data base. Byrepetitively executing the processing for each road section of an objectregion, it is possible to hold the compressed and coded shape data ineach road section included in the object region.

[0138] Thus, it is also possible to utilize, in an online processing,the result of resampling in the fixed length L for the road shape whichis executed in an offline.

[0139] (Fourth Embodiment)

[0140] In a fourth embodiment, description will be given to a method ofintroducing an irreversible compressing method to highly compress roadshape data.

[0141] In the transmission of voice data and image data, a processing iscarried out to decrease a sampling point within a negligible range inrespect of a sensation (visual sense/auditory sense) in order to enhancea compressibility, to decrease the quantization digit number ofmeasuring information or to manipulate the measuring information so asto increase the compressibility. In the case in which these processingsare executed, original data cannot be completely reconstituted on thereceiving side. In the case in which there is no hindrance even if thedata are varied more or less, the data can be considerably compressed bythe introduction of the irreversible compression processing.

[0142] In the position information transmitting method according to theinvention, the receiving side executes map matching to specify a roadshape. Therefore, it is necessary to transmit an accurate shape in thestart and end points of an object road section and a portion in whichmismatching is apt to be generated. In other portions, even if the shapeto be transmitted is slightly ambiguous, an original position can bespecified on the receiving side. Also in the position informationtransmitting method according to the invention, therefore, it ispossible to introduce an irreversible compressing method to increase thecompressibility of data to be transmitted.

[0143] In the compressing method according to the embodiment, thecompressibility of data is increased by the following method.

[0144] (1) To decrease a sampling point within such a range thatmismatching is not generated. On a highly curved road having a greatcurvature, a matching point is shifted from the road and the mismatchingmight be generated. For this reason, a sampling section length L is setbased on the curvature as shown in FIG. 12.

[0145] (2) To decrease a quantization digit number representing Δθwithin such a range that the mismatching is not generated For example, aminimum resolution is set to 2 degrees and Δθ is quantized in this unit.In this case, a reproduced node position is moved transversely around atrue value so that it is a matter of course that the reproduced shape isdeformed. For this reason, the receiving side carries out aninterpolation processing of smoothing the reproduced shape.

[0146] (3) To approximate the shape of the road to a circular arc and astraight line. In the case in which a value is caused to have adeviation in a difference expression based on a deviation anglestatistical predicted value S_(j) to carry out the compression andcoding, the deviation concentrates on zero in a road section having thesame curvature which is expressed in the circular arc or the straightline. Therefore, the statistical deviation is further increased so thata compression efficiency is rapidly increased. Accordingly, the shape ofthe road is approximated to the circular arc and the straight line sothat a compressibility can be rapidly enhanced. Moreover, the effect ofrun-length coding can also be increased.

[0147] The methods (1), (2) and (3) may be executed singly or incombination.

[0148] Description will be given to a specific example in which thecompression and coding is carried out by application of the methods (1),(2) and (3).

[0149] The approximation of the shape of the road to the circular arcand the straight line can be carried out by linearly approximating theshape of the road which is expressed in a full curvature function. Theshape of the road in which the point P_(J) on the road is expressed inthe full curvature function as shown in FIG. 1 is displayed as a solidcurved line in a coordinate system in which an axis of ordinateindicates θ(=Σθ_(j)) and an axis of abscissa indicates L (=ΣL_(i))(L_(i) is constant) as shown in FIG. 13. The approximation of the shapeof the road to the circular arc and the straight line indicates theapproximation of the curved line to a straight line (θ=aL+b) shown in adotted line. A straight line (θ=b) having an inclination=0 on thecoordinate system represents the linear shape of the road and a straightline (θ=aL+b) having an inclination of ≠0 represents the arcuate shapeof the road.

[0150] In the approximation, an allowable error is determined along aroad section by a method proposed separately by the inventors(JP-A-2001-129665 and JP-A-2001-132611). In the method, a tolerance (anallowable distance error) of an error (a distance error) for a distanceand a tolerance (an allowable azimuth error) of an error (an azimutherror) for an azimuth are set as allowable errors in order to satisfythe following conditions in a unit of each node or link included in theshape of a road.

[0151] {circle over (1)} The allowable distance error is set to be smallin the vicinity of the start and end points of an object road section.

[0152] {circle over (2)} In the case in which parallel roads areadjacent to each other, the allowable distance error is set to be small

[0153] {circle over (3)} The allowable distance error is set to be smallaround an intersection in which a connecting road having a smallintersection angle such as an interchange entrance or exist is present.

[0154] {circle over (4)} The allowable azimuth error is set to besmaller if a distance from a surrounding road is shorter.

[0155] {circle over (5)} There is a high possibility that the separationof the azimuth error might be increased in the portion of the road shapewhich has a great curvature. Therefore, the allowable azimuth error isset to be small.

[0156] Moreover, an allowable error in each node is set separately onthe left and right of an object road section. In the proposal, a methodof quantitatively calculating an allowable error in a unit of a node hasbeen described specifically.

[0157] If the allowable error is determined along the road section, theshape of the road is approximated to a circular arc and a straight lineso as to enter the range of the allowable error. As shown in FIG. 14,the shape of the road is divided into sections represented by thecircular arc or the straight line.

[0158] Next, respective resample section lengths of the sections aredetermined.

[0159] The resample section length is determined for each sectiondepending on a curvature a_(j) of each section j by the followingequation.

L _(j) =K×1/|a _(j)|

[0160] (K is a predetermined constant)

[0161] Moreover, the value of L_(j) may be quantized. If a value takenby L_(j) through the quantization is any of eight values of40/80/160/320/640/1280/2560/5120 meters, for example, the value of L_(j)can be coded to 3 bits to be transmitted.

[0162] At this time, if the resample section length L_(j) does notfluctuate between the adjacent sections, a compression efficiency can beincreased. FIG. 15(a) shows is a determining procedure for determining asection length to continue if a curvature is less changed in order tosuppress a fluctuation in a resample section length. From a firstsection (Step 30), a resample section length calculated value D_(j) isobtained from a curvature a_(j) of each section j in order (Step 31), achange rate H_(j) (=|D_(j)−D_(j−1)|/D_(j)) from a resample sectionlength calculated value D_(j−1) in an adjacent section is obtained (Step32), and furthermore, a ratio I_(j) (=D_(j)/L_(j−1))with a resamplesection length L_(j−1) in the adjacent section is obtained (Step 33).The change rate H_(j) of the resample section length calculated value iscompared with a predetermined constant H_(a), and furthermore, the ratioI_(j) with the resample section length L_(j−1) in the adjacent sectionis compared with predetermined values I_(a1) and I_(a2). When the ratioH_(j) is equal to or smaller than H_(a) and I_(j) has a value betweenI_(a1) and I_(a2), the resample section length L_(j) is set to be equalto the resample section length L_(j−1), in the adjacent section (Step35). The reason why the resample section length calculated value D_(j)is compared with the resample section length L_(J−1) in the adjacentsection is that the change rate H_(j) of the resample section lengthcalculated value D_(j) is small and the resample section length isthereby set to have the same value continuously in order to prevent theseparation of the resample section length calculated value D_(j) fromthe resample section length L_(j).

[0163] If the decision is NO at the Step 34, the section length L_(j) isdetermined from the value of D_(j) based on a lower table in FIG. 13 inwhich the relationship between the range of D_(j) and the section lengthis set (Step 36). This processing is executed for all the sections(Steps 37 and 38).

[0164] H_(a) is set to have a value of approximately 0.2, I_(a1) is setto have a value of approximately 0.7 and I_(a2) is set to have a valueof approximately 2.0.

[0165] As shown in FIG. 16, next, each section n is sampled in aresample section length L_(n) at regular intervals to obtain a nodeP_(J), and a quantized value of a predicted value difference Δθ_(j)(=θ_(j)−S_(j)) between a deviation angle θ_(j) of P_(J) and a deviationangle statistical predicted value S_(j) is calculated.

[0166] It is assumed that a deviation angle θ_(j−1) of a preceding nodeis used as the deviation angle statistical predicted value S_(j)(S_(j)=θ_(j−1)).

[0167] Moreover, the quantized value of Δθ_(j) is obtained with aminimum resolution Δθ_(j) set to be δ° (minimum resolution δ).

[0168] At this time, Δθ_(j) is set in a unit of δ. Therefore, a nodeP_(J+1) reproduced from the preceding node P_(J) based on a distanceL_(n) and angle information Δθ_(j) is not always positioned on theoriginal road shape (or an approximate shape). As shown in FIG. 17, whena next node P_(J+1) is to be obtained from P_(J), some candidate pointsof the node P_(J+1) appear by the way of taking the quantized value ofΔθ_(j). The next node P_(J+1) is selected from the candidate pointswithin the range of an allowable error such that a value of Δθ is set tobe zero as continuously as possible. Moreover, such a node selection iscontinuously carried out so that the node is to be selected in such adirection as to reduce an error between the position of the selectednode and a true value (a point on the original road shape) if the sameerror is increased to the vicinity of the limitation of an allowableerror. Also in this case, the node is selected such that Δθ iscontinuously set to be zero.

[0169]FIG. 18 shows a procedure for selecting one candidate point from aplurality of candidate points P_(J+1) (i) related to one node P_(J+1).

[0170] Step 40: Set the candidate point P_(J+1) (i) in a position with adistance of Ln, Δθ=δ·i from P_(J). i represents a quantized value of Δθto be (2m+1) positive and negative integers around zero having −m, . . ., −1, 0, 1, . . . , m.

[0171] Step 41: Calculate a distance D_(i) from each candidate pointP_(J+1) (i) to the closest point of the original road shape and an errorΔΘ_(i) between the intercept azimuth of the closest point and that ofthe candidate point P_(J−1) (i).

[0172] Step 42: Calculate an evaluation value ε_(i) for each candidatepoint P_(J+1) (i) by the following equation.

ε_(i)=α·(δ·|i|)+β·D _(i)+γ·|ΔΘ_(i)|+Ψ

[0173] α, β, γ: a predetermined coefficient

[0174] Ψ: a penalty value to be set if an allowable error range isexceeded

[0175] Step 43: Employ a candidate point P_(J+1) (i) having the smallestε_(i) for the node P_(J+1).

[0176] The evaluation value ε_(i) is a minimum with i=0 until D_(i) andΔΘ_(i) are increased and the penalty value Ψ is added thereto.Accordingly, the candidate point is employed such that Δθ is set to bezero.

[0177] Referring to the fraction of the section length D_(n) of thesection n, moreover, a processing is carried out in the followingmanner.

[0178] L_(n)<L_(n+1): The section n is resampled by the distance L_(n).If the remainder (fraction) of the section n is smaller than L_(n), asection n+1 and preceding sections are resampled by L_(n) such that adistance obtained by adding the fraction and a part of the section n+1,and this point and subsequent points in the section n+1 are resampled byL_(n+1).

[0179] L_(n)>L_(n+1): The section n is resampled by the distance L_(n).If the fraction of the section n is smaller than L_(n), this point inthe section n and the section n+1 are resampled by L_(n+1).

[0180] Thus, a deterioration in precision can be prevented by resamplingin a small section length.

[0181] If the minimum resolution δ° of Δθ is increased, therepresentation digit number of an angle is decreased and the shapefollowing property of a circular arc is deteriorated so that aprobability of Δθ=0 is reduced and the coding and compressing effectsare thereby deteriorated. To the contrary, if δ° is reduced, therepresentation digit number of the angle is increased and the shapefollowing property of a circular arc is enhanced so that the probabilityof Δθ=0 is increased and the coding and compressing effects are alsoenhanced. Moreover, the run-length compressing effects are alsoenhanced. In consideration of such a respect, it is necessary todetermine the minimum resolution δ° of Δθ which is to be used actually.

[0182] Next, description will be given to the coding of data in thiscase.

[0183] A predicted value difference Δθ of a corresponding node is codedsuch that a data length is reduced around Δθ=0.

[0184] A run-length of Δθ=0 is coded because most of To continuous dataare data on Δθ=0.

[0185] Moreover, a section length change code indicative of the changepoint of a resample section length is set. A special code is allocatedto the section length change code and the section length is defined byfixed bits (approximately 3 bits) provided immediately after the specialcode.

[0186] Furthermore, a reference point set code indicative of theidentification code of a reference point node in each section is set Aspecial code is allocated to the reference point set code, fixed bits(approximately 6 bits) provided immediately after the special code areset to be reference node numbers and coordinates appearing after thereference node numbers are defined as reference nodes (a node numberinitial value is predetermined without an overhead bit and it is alsopossible to use a node number architecture for adding one every time thecode is found).

[0187] Moreover, a special code is allocated as an EOD (End of Data)code indicative of the end of data. By the code, the end of a shape datastring representation is set.

[0188]FIG. 19 illustrates a code table to be used for the coding.

[0189] Furthermore, FIG. 20 shows a procedure for creating the codetable in an offline, and FIG. 21 shows a procedure for transmittingtraffic information in an online by using the code table. In FIG. 20,

[0190] Step 50: Refer to past traffic information.

[0191] Step 51: Select the object road section of the trafficinformation.

[0192] Step 52: Calculate an allowable error range along the object roadsection.

[0193] Step 53: Convert the node of the object road section into a fullcurvature function representation.

[0194] Step 54: Approximate the shape vector of the object road sectionto a circular arc and a straight line.

[0195] Step 55: Determine a resample length L_(n) of each section napproximating the circular arc or the straight line.

[0196] Step 56: Quantize and resample shape data on the object roadsection by L_(n) and set a node.

[0197] Step 57: Calculate Δθ of each section/each node in accordancewith a statistical value calculating equation.

[0198] Step 58: Calculate an occurrence distribution of Δθ.

[0199] Step 59: Calculate the continuous distribution of the same value.

[0200] Step 60: Create a code table based on the occurrence distributionof Δθ and the continuous distribution of the same value.

[0201] Step 61: Store the finished code table in a code table data base24.

[0202] Moreover, the online processing in FIG. 21 is carried out in thefollowing manner.

[0203] Step 62: Receive the traffic information from the eventinformation input portion 11.

[0204] Step 63: Select an object road section including the position ofgeneration of a traffic event.

[0205] Step 64: Calculate an allowable error range along the object roadsection.

[0206] Step 65: Convert the node of the object road section into a fullcurvature function representation.

[0207] Step 66: Approximate the shape vector of the object road sectionto a circular arc and a straight line.

[0208] Step 67: Determine a resample length L_(n) of each section napproximating to the circular arc or the straight line.

[0209] Step 68: Quantize and resample shape data on the object roadsection by L_(n) and set a node.

[0210] Step 69: Calculate Δθ of each section/each node in accordancewith a statistical value calculating equation.

[0211] Step 70: Convert the shape data into a code representation byreferring to the code table.

[0212] Step 71: Transmit the shape data on the coded object road sectiontogether with the traffic information.

[0213] While there has been described the example in which only the dataon the code table created in the offline processing are utilized in theonline processing, it is also possible to previously generate and storethe shape data of each road section in which each road shape of anobject region is represented by a code in the offline processing, toselect the coded road shape data of the road section including thetraffic event generation position from the shape data generated in theoffline processing when inputting the information about the generationof a traffic event in the online processing, to generate trafficinformation representing the traffic event generation position by therelative position of the road section, and to transmit, to the receivingside, the coded road shape data thus selected and the trafficinformation thus generated as described in the third embodiment. Thus,the resample result in the fixed length L for the road shape which isexecuted in the offline can also be utilized in the online processing.

[0214]FIG. 22 shows the road shape data to be transmitted. The datainclude code table data and the coded shape data, and include data suchas Δθ, the reference node of each section and a sample section length asthe coded shape data.

[0215]FIG. 23(a), (b), and (c) typically show data to be exchangedbetween transmission and receipt. On the transmitting side, a nodeposition after the quantization and resampling is calculated torepresent the road shape as shown in FIG. 23(a) and data indicative ofthe node position are transmitted to the receiving side as shown in FIG.23(b). The receiving side smoothens the received data and reproduces ashape as shown in FIG. 23(c). In this case, an interpolation based on aB spline (an interpolation curve such as a Beziers spline or a Bezierscurve is available) or smoothing based on a smoothing function can becarried out. Moreover, the intercept azimuth of each interpolation pointwhich is generated is also distributed averagely.

[0216]FIG. 24 shows the procedure of the receiving side.

[0217] Step 80: Receive position information.

[0218] Step 81: Convert the shape data of a code representation into afull curvature function by referring to a code table.

[0219] Step 82: Next, carry out a conversion into latitude and longitudecoordinates and a smoothing and interpolation processing to reproducethe shape data.

[0220] Step 83: Acquire a reference node position.

[0221] Step 84: Carry out map matching to specify an object roadsection.

[0222] Step 85: Reproduce the traffic information.

[0223] Thus, the shape data are highly compressed by using theirreversible compressing method described in the embodiment so that thevolume of data to be transmitted can be reduced considerably.

[0224] The circular arc and straight line approximation of the shapedata represented by the full curvature function can also be carried outsimultaneously with the quantization resampling except that the shape isapproximated in advance as described above.

[0225] The decision logic of the resample section length and theprocedure for determining the quantization resampling which have beendescribed above can also be applied to the case in which the shape dataare not approximated to the circular arc.

[0226] (Fifth Embodiment)

[0227] In a fifth embodiment, description will be given to a method ofcoding road shape data without using the resample of a coordinate point.

[0228] As described above with reference to FIG. 41, a coordinate point(P_(J)) arranged on a road can be uniquely specified by two dimensionsof a distance from an adjacent coordinate point (P_(J−1)) and an angle.In the first to fourth embodiments, the position of the coordinate pointis resampled such that the distance becomes constant, and only the angleis coded to reduce the volume of data to be transmitted- In this case,however, a resample processing is required.

[0229] On the other hand, in the case in which road shape data are to becoded by exactly using, for the coordinate point, a node and aninterpolation point which are included in the road shape of a digitalmap, the resample processing is not required. In this case, the distanceof the node or the interpolation point is not constant. Therefore, it isnecessary to code the angle and the distance.

[0230]FIG. 25 shows a method of coding both the angle and the distance.The coding of the angle is the same as that in the first embodiment, andangle information of each node (including an interpolation point) P_(J)is represented by a predicted value difference Δθ_(j) to be a differencebetween a deviation angle θ_(j) and a deviation angle statisticalpredicted value S_(j), Δθ_(j) is quantized in a unit of 1° (anotherresolution such as a unit of 2° may be used), for example, and a codetable for Δθ is created based on the frequency of generation of thequantized Δθ_(j). At this time, the deviation angle statisticalpredicted value S_(j) is defined as S_(j)=θ_(j−1) orS_(j)=(θ_(j−1)+θ_(j−2))/2, for example.

[0231]FIG. 26(b) shows an example of the code table for Δθ thus created.The table is the same as the code table (FIG. 2) according to the firstembodiment. By using the code table for Δθ, the angle information(Δθ_(j)) of each node is viable-length coded.

[0232] On the other hand, the distance is coded in the following manner.

[0233] First of all, the distance information of each node P_(J) isrepresented by a predicted value difference ΔL_(j) (=L_(j)−T_(j)) to bea difference between a distance L_(j) to an adjacent node P_(J+1) and adistance statistical predicted value T_(j), and ΔL_(j) is quantized in aunit of 10 m (another resolution such as a unit of 50 m or 100 m may beused), for example. At this time, the distance statistical predictedvalue T_(j) is defined as T_(j)=L_(j−1) or T_(j)=(L_(j−1)+L_(j−2))/2,for example.

[0234] Next, a code table for ΔL is created based on the frequency ofgeneration of the quantized ΔL_(j). FIG. 26(a) shows an example of thecode table for ΔL thus created. The overhead bit of the code table is tobe added for representing the positive or negative sign of ΔL. When ΔL≠0is set, 0 is added if ΔL is positive, and 1 is added if ΔL is negative.Accordingly, if T_(j)=L_(j−1) is defined,

[0235] when L_(j) is greater than L_(j−1) (L_(j)−L_(j−1)>0), 0 is added,and

[0236] when L_(j) is smaller than L_(j−1) (L_(j)−L_(j−1)<0), 1 is added.

[0237] By using the code table for ΔL, the distance information (ΔL_(j))of each node is variable-length coded.

[0238] The order of a data array for coding the distance and angle ispredetermined as ΔL_(j)→Δθ_(j)→ΔL_(j+1)→Δθ_(j+1)→. . . . When an arrayof ΔL−Δθ is set to

[0239] “0·0_(—)0·0_(—)0·−2_(—)+2·−2_(—)0·+3_(—)−5·0_(—)0·0_(—)0·+6”, thedata string is variable-length coded by using the code tables of FIGS.26(a) and (b) in the following manner.

[0240]0·0_(—)0·0_(—)0·1011_(—)1010·1011_(—)0·11000_(—)11101·0_(—)0·0_(—)0·111100”→

[0241] “00000101110101011011000111010000111100” (38 bits).

[0242] If a distance component is represented by a fixed length of 8bits and an angle component is represented by a fixed length of 10 bits,(8 bits+10 bits)×8 nodes=144 bits are required so that a data volume canbe compressed to 26% by the variable-length coding.

[0243]FIG. 27 shows a processing procedure for creating these codetables in an offline. With reference to past traffic information (Step90), first of all, the object road section of the traffic information isselected (Step 91). Position data on a node included in the object roadsection are converted into a full curvature function representation(Step 92) and ΔL_(j) and Δθ_(j) in each node of each section arecalculated in accordance with a statistical value calculating equation(Step 93). Next, the occurrence distributions of ΔL_(j) and Δθ_(j) arecalculated (Step 94) and a code table for ΔL is created based on theoccurrence distribution of ΔL_(j), and furthermore, a code table for Δθis created based on the occurrence distribution of Δθ_(j) (Steps 95 and96).

[0244] Moreover, FIG. 28 shows a processing procedure for coding roadshape data by using the created code table in order to transmit thetraffic information. When the traffic information is received (Step 97),an object road section including the position of generation of a trafficevent is selected (Step 98). Position data on a node included in theobject road section are converted into a full curvature functionrepresentation (Step 99), and ΔL_(j) and Δθ_(j) in each node of eachsection are calculated in accordance with a statistical valuecalculating equation (Step 100). Next, ΔL_(j) and Δθ_(j) in each nodeare converted into a code representation by referring to the code tabledata of the code table created to be intended for the object roadsection (or a code table created to be intended for a road taking ashape approximating the object road section) (Step 101). Shape data onthe object road section thus coded are transmitted together with data onan event position represented by relative information in the object roadsection (step 102).

[0245]FIG. 29 and FIG. 30 show road shape data (FIG. 29) and eventposition data (FIG. 30) which are to be transmitted. The road shape datainclude code table data, the absolute coordinates of a start node p1 ofa section (nodes p1 and p2) to be represented by a code, the absoluteazimuth of the node p1, a distance L from the node p1 to a next node,and coded data between the nodes p1 and p2 (a bit string having ΔL_(j)and Δθ_(j) coded).

[0246] On the receiving side where the data are received, the datarepresented by a code are converted into a full curvature function byreferring to the code table, thereby reproducing road shape data in thesame manner as in a processing flow of FIG. 11. Next, map matching ofthe reproduced shape and the road shape of a self-digital map isexecuted to specify an object road section and to specify a trafficevent generation position in the object road section from the eventposition data.

[0247] In the method according to the embodiment, thus, the coordinatepoint is not resampled but both data on the angle and distance forspecifying the coordinate point are variable-length coded so that thetransmission data volume of the road shape data can be reduced.

[0248] (Sixth Embodiment)

[0249] In a sixth embodiment, description will be given to a method ofresampling the position of a coordinate point to cause an anglecomponent to be constant on a road, thereby coding only a distancecomponent.

[0250] As described above with reference to FIG. 41, a coordinate point(P_(J)) arranged on a road can be uniquely specified by two dimensionsof a distance from an adjacent coordinate point (P_(J−1)) and an angle.In the first to fourth embodiments, the position of the coordinate pointis resampled to cause the distance of the two dimensions to be constant,thereby coding only the angle to reduce the volume of data to betransmitted. To the contrary, the position of the coordinate point isresampled to cause the angle to be constant, thereby coding only thedistance to reduce the volume of data to be transmitted in the sixthembodiment.

[0251]FIG. 31 shows a resample coordinate point in the case in whichangle information is fixed (deviation angle θ=constant) and distanceinformation is coded. A processing of resampling the shape data iscarried out in the following manner.

[0252] (1) Tracing is carried out over the road shape from a start nodeP₀ toward an end node and a next node P₁ is set into a position in whicha deviation angle reaches a predetermined angle θ (or −θ).

[0253] (2) When the tracing is carried out in the (1) and a distancefrom the start node P₀ reaches a predetermined distance L_(max) beforethe deviation angle reaches θ (or −θ), a next node P₁ is set into thatposition.

[0254] (3) By setting the node P₁ determined in the (1) or (2) to be astart edge, the rules of the (1) and (2) are applied to determine a nextnode P₂ and this processing is sequentially repeated to determine P₃, .. . , P_(J), . . . .

[0255] Distance information in each node P_(J) which is resampled isrepresented by a predicted value difference ΔL_(j) (=L_(j)−T_(j)) to bea difference between a distance L_(j) to an adjacent node P_(J+1) and adistance statistical predicted value T_(j), and ΔL_(j) is quantized in aunit of 10 m (another resolution such as a unit of 50 m or 100 m may beused), for example. At this time, the distance statistical predictedvalue T_(j) is defined as T_(j)=L_(j−1) or T_(j)=(L_(j−1)+L_(j−2))/2,for example.

[0256] Next, a code table for ΔL is created based on the frequency ofgeneration of the quantized ΔL_(j). At this time, a continuousdistribution of ΔL_(j) may be calculated to create a code tableincorporating run-length coding.

[0257]FIG. 32 shows an example of the code table for ΔL thus created. Inthe code table, it is defined that one bit for representing the positiveor negative sign of the deviation angle θ (0 if θ is positive and 1 if θis negative) is added as an overhead bit to a code when ΔL=0 is set, andfurthermore, it is defined that two bits having one bit for representingthe positive or negative sign of the deviation angle θ and one bit (0 ifΔL is positive and 1 if ΔL is negative) for representing the positive ornegative sign of ΔL are added as overhead bits to the code when ΔL≠0 isset. Accordingly, in the case in which T_(j)=L_(j−1) is defined,

[0258] when ΔL≠0 is set,

[0259] if L_(j) is greater than L⁻¹ (L_(j)−L_(j−1)>0), 0 is added as anoverhead bit for representing the positive or negative sign of ΔL, and

[0260] if L_(j) is smaller than L_(j−1), (L_(j)−L_(j−1)<0), 1 is addedas the overhead bit for representing the positive or negative sign ofΔL, and furthermore,

[0261] if an azimuth of P_(j−1)→P_(j) is provided on the left side of anazimuth of P_(j−2)→P_(j−1), (left curve), 0 is added as the overhead bitfor representing the positive or negative sign of θ, and

[0262] if the azimuth of Pj−1→Pj is provided on the right side of theazimuth of Pj−2→Pj−1 (right curve), 1 is added as the overhead bit forrepresenting the positive or negative sign of θ.

[0263] In the fourth embodiment, the description has been given to theexample in which the distance component (resample section length) ischanged depending on the section in the case in which the coordinatepoint is resampled to cause the distance component to be constant. Alsoin the case in which the resampling is carried out to cause the anglecomponent to be constant, it is also possible to change the value of θdepending on the section. In this case, the value of θ in each sectioncan be identified by using a special code over a code converted shapedata string in the same manner as in the fourth embodiment.

[0264]FIG. 33 shows a processing procedure for creating the code tablein an offline. Moreover, FIG. 34 shows a processing procedure for codingroad shape data by using the code table thus created and transmittingtraffic information. These procedures are different from the proceduredescribed in the third embodiment (FIG. 7 and FIG. 8) in that the shapedata on an object road section are resampled with a fixed angle θ (or−θ) in place of a fixed length L (Step 112, Step 121), ΔL is calculatedin place of Δθ of each node which is resampled (Step 114, Step 123) anda code table for ΔL is created based on a distribution of ΔL in place ofa code table for Δθ based on the distribution of Δθ (Step 115, Step117), and other procedures are identical.

[0265] Moreover, FIG. 35 shows road shape data to be transmitted. Theroad shape data are different from the road shape data described in thethird embodiment (FIG. 9) in that they include information about asample angle θ in place of a sample section length L, and furthermore,include a bit string having ΔL_(j) coded as the coded data in place of abit string having Δθ_(j) coded, and other respects are identical.

[0266] On the receiving side where the data are received, datarepresented by a code are converted into a full curvature function withreference to a code table to reproduce the road shape data in the samemanner as in the processing flow of FIG. 11. Next, map matching with thereproduced shape and the road shape of a self-digital map is executed tospecify an object road section and to specify a traffic event generationposition in the object road section from event position data.

[0267] In the method according to the embodiment, thus, the position ofthe coordinate point is resampled to cause the angle component to beconstant over a road and only the distance component is variable-lengthcoded so that the transmission data volume of the road shape data can bereduced.

[0268] (Seventh Embodiment)

[0269] In a coding method according to a seventh embodiment, arepresentation based on a deviation angle or a representation based on apredicted value difference can be selected as a method of representingangle information in order to convert the shape of a road into shapedata having a statistical deviation.

[0270] As described above with reference to FIGS. 42, in the case inwhich any of the representation based on the deviation angle θ_(j)(FIGS. 42(b) and (b′)) and a representation based on the predicted valuedifference Δθ_(j) of the deviation angle θ_(j) (FIGS. 42(c) and (c′)) isemployed for the angle information of a coordinate point, road shapedata can be converted into data having a statistical deviation.

[0271] If the statistical deviation is greater, the effect of reducing adata volume based on variable-length coding is increased. In comparisonof the case in which the angle information of the coordinate point isrepresented by the deviation angle θ_(j) with the case in which the sameangle information is represented by the predicted value differenceΔθ_(j) of the deviation angle θ_(j), the latter case generally providesa greater statistical deviation.

[0272] As shown in FIG. 36, however, if the angle information isrepresented by the predicted value difference Δθ_(j) of the deviationangle in a road 40 having a straight line provided between curves for awhile, 0, . . . , 0, θ₁, −θ₁, 0, . . . , 0, θ₂, −θ₂, 0, . . . is set,and if the angle information is represented by the deviation angle θ,

[0273] 0, . . . , 0, θ₁, 0, 0, . . . , 0, θ₂, 0, 0, . . . is set. In thecase in which the angle information of the coordinate point isrepresented by the deviation angle θ_(j), it can have a greaterstatistical deviation as compared with the case in which the angleinformation of the coordinate point is represented by the predictedvalue difference Δθ_(j).

[0274] In some cases, thus, it is preferable that the angle informationof the coordinate point resampled with a constant distance L should berepresented by the deviation angle θ_(j) to be suitable forviable-length coding depending on the shape of the road.

[0275] In the method according to the embodiment, a data size obtainedby representing the shape of the road by the deviation angle θ to carryout the variable-length coding is compared with a data size obtained byrepresenting the shape of the road by the predicted value difference Δθof the deviation angle to carry out the variable-length coding totransmit coded data having the smaller data size.

[0276] First of all, there are created a deviation angle θ code tablefor representing the shape of the road by the deviation angle θ_(j) tocarry out the variable-length coding and a Δθ code table forrepresenting the shape of the road by the predicted value differenceΔθ_(j) of the deviation angle θ_(j) to carry out the variable-lengthcoding.

[0277]FIG. 37 shows a procedure for creating a deviation angle θ codetable and FIG. 38 shows a procedure for creating a Δθ code table. Theprocedure shown in FIG. 38 is the same as the procedure (FIG. 7) in thethird embodiment. Moreover, the procedure shown in FIG. 37 is differentin that the deviation angle θ is used in place of Δθ in the procedureshown in FIG. 38.

[0278]FIG. 39 shows a processing procedure for coding road shape dataand transmitting traffic information by using these code tables createdin offline.

[0279] Step 130: Receive traffic information.

[0280] Step 131: Select an object road section including the position ofgeneration of a traffic event.

[0281] Step 132: Resample the road shape data of the object road sectionin a fixed length L and set a node.

[0282] Step 133: Convert the position data of the set node into a fullcurvature function representation.

[0283] Step 134: Next, create code data on θ by referring to a codetable for θ and calculate a data size (A).

[0284] Step 135: Next, create code data on Δθ by referring to a codetable for Δθ and calculate a data size (B).

[0285] Step 136: Compare the data size (A) with the data size (B),employ an angle representation of the smaller data size and set, toshape data to be transmitted, a value of an “angle representationidentification flag” indicative of the angle representation thusemployed and “coded data” in the employed angle representation.

[0286] Step 137: Transmit the shape data on the coded object roadsection together with data on an event position expressed in therelative information of the object road section.

[0287]FIG. 40 shows the road shape data to be transmitted. The roadshape data include information about the “angle representationidentification flag” indicative of the employed angle representation (0when a representation based on the deviation angle θ is employed, and 1when a representation based on the predicted value difference Δθ isemployed) and information about the “coded data” in the employed anglerepresentation.

[0288] On the receiving side where the data are received, θ or Δθ isreconstituted from the “coded data” represented by a code with referenceto the code table based on information designated by the “anglerepresentation identification flag”, thereby converting position data oneach node into a full curvature function Subsequent processings are thesame as those in the third embodiment, and the road shape data arereproduced, map matching of the reproduced shape and the road shape of aself-digital map is executed to specify an object road section and tospecify a traffic event generation position in the object road sectionfrom event position data.

[0289] In the method according to the embodiment, thus, any of therepresentation based on the deviation angle or the representation basedon the predicted value difference is selected as the method ofrepresenting angle information. Consequently, the volume of data to betransmitted can be reduced still more.

[0290] The coding method according to the invention can also be appliedto the compression of a map data body. Moreover, the method can also beapplied to the transfer of map data over an internet (for example, aclient-server type map display system using a vector map) or a map datadelivery service.

[0291] Also in the case in which running locus data are to betransmitted to a center for an urgent report sent from the onboardmachine of a vehicle or floating car data (FCD), moreover, the data canbe compressed by using the coding method.

[0292] Also in the case in which a vector shape is to be compressed in aspline compressing method and is to be transmitted as data on each nodestring, furthermore, data compression can be carried out over therepresentation of the node string by using the code table with theapplication of the coding method according to the invention.

[0293] Moreover, the coding method according to the invention can alsobe applied to the case in which the shape data of a region (polygon) ona digital map are to be transmitted. For example, in the case in whichthe polygon is to be designated to transmit a weather report in theregion, the shape data of a border line on the polygon shape aretransmitted so that the receiving side can specify the polygon. In thecase in which the shape data of the border line are to be transmitted,the transmission data volume can be compressed by applying the codingmethod according to the invention. At this time, in the case in which itis not necessary to precisely specify the polygon shape as in the regionin which the weather report is applied, the receiving side can omit amatching processing with the shape on the digital map.

[0294] The illustrated code table is only an example and is not alwaysoptimum. Actually, it is necessary to check the distribution of thevariable (θ_(j), Δθ_(j), L_(j)), thereby creating a code table by usingthe Huffman tree.

[0295] For the coding technique, there are various methods such as afixed character compressing method, a run-length method, a Shannon-Fanocoding method, a Huffman coding method, an adaptive type Huffman codingmethod, an arithmetic coding method and a dictionary method (LHAmethod). In this specification, it is also possible to use these codingmethods While the description has been given to the case in which thecode table is generated in an offline, the coding can be carried out inan online by using the adaptive type Huffman coding method or thearithmetic coding method.

[0296] While only certain embodiments of the invention have beenspecifically described herein, it will be apparent that numerousmodifications may be made thereto without departing from the spirit andscope of the invention.

[0297] The present invention is based on Japanese Patent ApplicationsNo. 2001-134318 filed on May 1, 2001 and No. 2001-220061 filed on Jul.19, 2002, which are incorporated herein by references.

[0298] <Industrial Applicability>

[0299] As is apparent from the above description, in the coding methodaccording to the invention, the data volume of the vector shape on thedigital map can be compressed efficiently. In the position informationtransmitting method and device according to the invention, consequently,it is possible to considerably decrease the transmission data volume inthe case in which the vector shape of the digital map is to betransmitted. On the receiving side, the shape data are reconstitutedfrom the received data and the map matching is carried out so that thevector shape thus transmitted can be specified accurately.

1. A shape vector data coding method of coding data representing a shapevector on a digital map, wherein an arithmetic processing is carried outover position information about each node of a node string representingthe shape vector, the position information is converted into data havinga statistical deviation, and the data are coded to reduce a data volume.2. The shape vector data coding method according to claim 1, wherein theposition information about the node is expressed in information about adistance from an adjacent node and an angle of a straight line extendedfrom the adjacent node, and the distance or angle is expressed in datahaving a statistical deviation, thereby coding the data.
 3. The shapevector data coding method according to claim 1 or 2, wherein theposition information about the node is converted into difference datafrom a statistical predicted value and the difference data are coded. 4.The shape vector data coding method according to claim 2, wherein theinformation about the angle is expressed in a deviation angle and thedeviation angle is coded.
 5. The shape vector data coding methodaccording to claim 2, wherein the information about the angle isexpressed in a difference for a statistical predicted value of thedeviation angle and the difference is coded.
 6. The shape vector datacoding method according to claim 2, wherein the information about thedistance is represented by a difference for a statistical predictedvalue of the distance and the difference is coded.
 7. The shape vectordata coding method according to claim 1 or 2, wherein the node isresampled such that at least one element in the position informationabout the node takes a constant value in a predetermined section of theshape vector.
 8. The shape vector data coding method according to claim7, wherein the node is resampled in such a position that a distance froman adjacent node is equal, and the position information about the nodeis represented by only angle information.
 9. The shape vector datacoding method according to claim 7, wherein the node is resampled insuch a position that a deviation angle of a straight line extended froman adjacent node takes a constant angle, and the position information ofthe node is represented by only distance information.
 10. The shapevector data coding method according to claim 7, wherein the shape vectoris divided into a plurality of sections and the constant value is setfor each section.
 11. The shape vector data coding method according toclaim 10, wherein a constant resample section length is set for thesection and the node is resampled at an interval of the resample sectionlength.
 12. The shape vector data coding method according to claim 1 or2, wherein an arithmetic processing is carried out over positioninformation about a node or an interpolation point which is included inthe shape vector of the digital map and the position information isconverted into data having a statistical deviation.
 13. The shape vectordata coding method according to claim 1, wherein an arithmeticprocessing is carried out over information about a node string of aspline function approximating the shape vector to be converted into datahaving a statistical deviation.
 14. The shape vector data coding methodaccording to claim 1 or 2, wherein the data are variable-length coded toreduce a data volume.
 15. The shape vector data coding method accordingto claim 1 or 2, wherein the data are run-length coded to reduce a datavolume.
 16. The shape vector data coding method according to claim 11,wherein the resample section length is set depending on a curvature ofthe shape vector.
 17. The shape vector data coding method according toclaim 1, wherein an allowable error of the shape vector is calculatedand a quantized digit number is decreased when the data are coded so asnot to exceed the allowable error.
 18. The shape vector data codingmethod according to claim 16, wherein the shape vector is approximatedby a circular arc and a straight line, and the resample section lengthis set for each section of the approximated circular arc or straightline.
 19. A position information transmitting method for a digital mapin which a transmitting side transmits shape data representing a shapevector on the digital map and a receiving side carries out map matchingbased on the received shape data and specifies the shape vector on aself-digital map, wherein the transmitting side transmits shape vectordata coded by the coding method according to any of claims 1 to 18 andthe receiving side decodes the received data and reproduces a shape, andspecifies a shape vector corresponding to the reproduced shape by themap matching.
 20. The position information transmitting method accordingto claim 19, wherein the transmitting side transmits data including acode table used for coding and the receiving side reproduces a shape byusing the received code table.
 21. The position information transmittingmethod according to claim 19, wherein the transmitting side sets aresample section length within such a range that mismatching is notgenerated on the receiving side.
 22. The position informationtransmitting method according to claim 19, wherein the transmitting sidedecreases a quantized digit number within such a range that mismatchingis not generated on the receiving side.
 23. The position informationtransmitting method according to claim 19, wherein the transmitting sideapproximates the shape vector by a circular arc and a straight linewithin such a range that mismatching is not generated on the receivingside.
 24. The position information transmitting method according toclaim 19, wherein the transmitting side previously creates and holds acode table to he used for coding and codes the shape vector by using thecode table.
 25. The position information transmitting method accordingto claim 24, wherein the transmitting side previously holds data on theshape vector coded by using the code table and selects data to betransmitted from the held data.
 26. The position informationtransmitting method according to claim 19, wherein the transmitting sidetransmits data representing a shape of a polygon on the digital map asthe coded shape vector data.
 27. A transmitter for transmitting, to areceiving side, shape data representing a shape vector on a digital mapfor specifying a shape by map matching, comprising: code tablecalculating means for carrying out an arithmetic processing overposition information of each node of a node string representing theshape vector on the digital map, converting the position informationinto data having a statistical deviation and generating a code tableusing coding for the data based on an occurrence distribution of thedata; and position information converting means for coding positioninformation of each node of the shape vector to be transmitted to thereceiving side by using the code table and for generating shape data tobe transmitted to the receiving side.
 28. A transmitter fortransmitting, to a receiving side, shape data representing a shapevector on a digital map for specifying s shape by map matching,comprising; position information converting means for coding positioninformation of each node of the shape vector to be transmitted to thereceiving side by using a code table generated by means of anotherdevice and for generating the shape data to be transmitted to thereceiving side.
 29. A receiver for receiving shape data representing ashape vector on a digital map from a transmitting side and for carryingout map matching to specify the shape vector on a self-digital map,comprising: code data decoding means for decoding the received datawhich are coded and for reproducing the shape data represented byposition information on the digital map; and map matching means forcarrying out map matching by using the shape data thus reproduced,thereby specifying the shape vector on the self-digital map.
 30. Aprogram of a transmitter for transmitting, to a receiving side, shapedata representing a shape vector on a digital map for specifying a shapeby map matching, wherein a computer is caused to execute: a procedurefor resampling the shape vector on the digital map in a fixed length,thereby setting a node; a procedure for carrying out an arithmeticprocessing over position data of the node to be converted into datahaving a statistical deviation; and a procedure for generating a codetable to be used for coding the data based on an occurrence distributionof the data having a statistical deviation.
 31. A program of atransmitter for transmitting, to a receiving side, shape datarepresenting a shape vector on a digital map for specifying a shape bymap matching, wherein a computer is caused to execute: a procedure forresampling the shape vector in a fixed length, thereby setting a node; aprocedure for carrying out an arithmetic processing over position dataof the node to be converted into data having a statistical deviation;and a procedure for converting the data having a statistical deviationinto a code representation by referring to a code table.
 32. A programof a receiver for receiving shape data representing a shape vector on adigital map from a transmitting side and for carrying out map matchingto specify the shape vector on a self-digital map, wherein a computer iscaused to execute: a procedure for decoding the received data which arecoded by referring to a code table; a procedure for reproducing shapedata represented by position information on the digital map from thedecoded data; and a procedure for carrying out map matching by using theshape data thus reproduced, thereby specifying the shape vector on theself-digital map.